Tong-Seok Han

Analysis on Anisotropy of Void Distribution and Stiffness of Lightweight Aggregate using CT Images

The void distribution in concrete materials strongly affects its material properties. Therefore, the identification of spatial distribution of void is important to understand and estimate material behavior. To examine and quantify the void distribution inside lightweight aggregates, CT(computed tomography) image is used. 3D lightweight aggregate images are generated by stacking of cross-sectional images from CT. Spatial distribution of void of aggregate along the direction is visualized on the sphere using probability distribution function. Stiffness of lightweight aggregate for the directions is also examined. It is confirmed that direction-based probability distribution and stiffness from CT images are effective in characterizing void distributions of aggregates.

Spatial Distribution of Voids in Insulating Concrete Analyzed by Micro-CT Images and Probability Functions

Insulating concrete is a multiphase material designed for reduced thermal conductivity, and the void distribution in concrete strongly affects its physical properties such as mechanical response and heat conduction. Therefore, it is essential to develop a method for identifying the spatial distribution of voids. To examine the voids of insulating concrete specimens, micro-CT (computed tomography) images can be effectively used. The micro-CT images are binarized to visualize the void distribution and stacked to generate 3D specimen images. From the obtained images, the spatial distribution of the voids and the microscopic constituents inside the insulating concrete specimens can be identified. The void distribution in the material can be characterized using low-order probability functions such as two-point correlation, lineal-path, and two-point cluster functions. It is confirmed that micro-CT images and low-order probability functions are effective in describing the relative degree of void clustering and void connectivity in insulating concrete.

Characterization of Fiber Connectivity in Fire-resistant High Strength Concrete using Percolation Theory

To improve fire-resistance of a high strength concrete against explosive spalling under elevated temperature, fibers can be mixed with concrete to provide flow paths of evaporated water within concrete to the free surface. The fiber-mix concrete approach is effective against explosive spalling when the flow path generated from melting fibers at the elevated temperature is interconnected to transport high pressurized evaporated water from the inside concrete to the free surface. The percolation theory can identify the connectivity of the fibers and provide an estimate of the fire-resistance of concrete by investigating layout of fibers. In this study, the correlation between percolation theory and explosive spalling of fiber-mixed high strength concrete is analyzed and the connectivity of the fiber in concrete is stereologically investigated by using virtual specimens of fiber-mixed high strength concrete.

Analysis of Constituents of Insulating Concrete using Micro CT Images

Concrete is a multi-phase material whose material properties are affected by spatial distributions of phases. The void distribution in concrete strongly affects physical properties of materials, such as mechanical response and heat conduction. To examine constituents of insulating concrete specimens, micro CT(micro computed tomography) image can be effectively used. Using micro CT images, the spatial distribution of constituents in insulating concrete, such as aggregates and glass beads to ensure the dispersed void distribution, can be detected. It is confirmed that micro CT images are effective in describing the spatial distribution of constituents of insulating concrete.

Reconstruction of Two-phase Polycrystalline Microstructures of Mechanical Isotropy

Understanding of the phase distribution in a multi-phase polycrystalline material is important because it can affect material properties and mechanical behaviors significantly. In this research, probability functions (two-point correlation and lineal-path functions) are used to represent the phase distributions of microstructures. The two-phase microstructures with random phase distribution are reconstructed using probability functions and compared with original samples. Mechanical behaviors of the virtual samples for different directions are evaluated using a finite element method. It is confirmed that microstructures with the same statistical characteristics can be generated using the reconstruction method. It is also demonstrated that the characteristics of the probability functions and mechanical reponses between the original and reconstructed microsturctures are statistically identical.

Study on The Heat Transfer and Mechanical Modeling of Fiber-Mixed High Strength Concrete

To improve fire-resistance of a high strength concrete against spalling under elevated temperature, fibers can be mixed to provide flow paths of evaporated water to the surface of concrete when heated. In this study, the experiment of a column under fire and mechanical loads is conducted and the material model for predicting temperature of reinforcement steel bar and mechanical behavior of fiber-mixed high strength concrete is suggested. The material model in previous studies is modified by incorporating physical behavior of internal concrete and thermal characteristics of concrete at the elevated temperature. Thermo-mechanical analysis of the fiber-mixed high strength concrete column is conducted using the calibrated material model. The performance of the proposed material model is confirmed by comparing thermo-mechanical analysis results with the experiment of a column under fire and mechanical loads.

Evaluation of Effect of Plastic Gradient on the Behavior of Single Grain inside Polycrystalline Solids

Plastic gradient from geometrically necessary dislocation(GND) can strongly affect micro-scale plastic behavior of polycrystalline solids. In this research, mechanical behavior of polycrystalline solid is investigated using the finite element method incorporating plastic gradient from GND effect. Gradient hardness coefficient and material length parameter are used to evaluate the effect of the plastic gradient on the behavior of materials. Sensitivity of the modeling parameters on the plastic gradient from GND is presented and effects of plastic gradient and material parameters on the behavior of single crystal inside a polycrystalline aggregate are investigated. It is confirmed that the plastic gradient from GND amplifies hardening response of polycrystals and affects single crystal behavior embedded in polycrystalline solids.

Analysis of Correlation between Percolation of Porous Concrete and Probability Distribution Functions

Concrete is a multi-phase material of which material properties are strongly affected by the phase distribution. Spatial distribution of pore in concrete affects mechanical behavior and percolation significantly. Therefore, a proper method to describe the pore distribution of a material is needed. CT(computed tomography) image is used to examine and to quantify the pore distribution of porous concrete specimens. 3D concrete digital specimens base on the real concrete with different pore ratio are created by subsequent stacking of 2D cross-sectional images from CT. Probability distribution functions such as two-point correlation, lineal-path and two-point cluster functions are used for pore distribution characterization. Correlation between hydraulic conductivity from experiment and probability distribution functions of porous concrete is examined using CT image processing. It is confirmed that probability distribution functions based on CT images are effective in characterizing pore distributions including pore clustering and percolation.